AI code review for nontechnical people.
You do not have to understand every line of code to review AI-generated software. You need to check whether the thing works, whether the proof is real, and whether the risky parts were touched.
Use this before accepting AI-generated code.
If the agent cannot answer these in plain English, the work is not ready.
- Where can I open the exact thing a user would use?
- What changed, in plain English?
- What did you test yourself?
- What risky files, settings, or accounts did you avoid?
- What is still not proven?
The free checks.
Open the real surface.If customers use a public page, open the public page. If the work is a download, download the file. If it is a payment flow, open checkout and confirm the product name and price.
Ask for proof that matches the goal.A passing test is useful, but it does not prove a public page, a Stripe checkout, an email, or a scheduled automation worked for a real user.
Look for quiet collateral damage.Ask what files, settings, accounts, routes, or database tables changed. The answer should be specific enough that another agent could inspect it.
Reject vague confidence."It should work now" is not evidence. Ask for the exact URL, screenshot, command output, receipt, or dashboard item.
Keep one next step.If the result is not fully proven, the next step should be one concrete action, not a paragraph of maybe-this-maybe-that.
The trap
Reading code line by line is the wrong job for most operators. Your job is to decide whether the original business outcome is now true. The proof has to match that outcome.
What the $1 checklist adds.
The paid download gives you the reusable handoff brief, 15 acceptance checks, proof menus, a completion receipt prompt, red flags, and copy-paste follow-up lines for weak AI-agent answers.